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157 lines
20 KiB
Plaintext
157 lines
20 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"jukit_cell_id": "4yTe29l2Ya"
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},
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"source": [
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"# Document Loaders\n",
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"\n",
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"- loading text from local sources\n",
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"- main driver is `Unstructured` python package\n",
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"\n",
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"## Key Concepts\n",
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"\n",
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"### Document\n",
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"\n",
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"container class for document information. contains:\n",
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" - page_content\n",
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" - metadata\n",
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"\n",
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"### Loader\n",
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"\n",
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"base class to load documents. exposes:\n",
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" - load() -> Document\n",
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"\n",
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"\n",
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"## Setup Unstructured\n",
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"- host dependencies\n",
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" - poppler: PDF rendering library\n",
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"- Python deps:\n",
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" - Pillow: imaging library"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "srwyN0cVES"
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},
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"source": [
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"# %pip install pillow (already installed)\n",
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"%pip install -q unstructured[local-inference]"
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],
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": "Note: you may need to restart the kernel to use updated packages.\n"
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}
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],
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"execution_count": 1
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "cbFv0eSeXq"
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},
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"source": [
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"docs_dir=\"unstructured-examples\"\n",
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"!mkdir -p $docs_dir\n",
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"!wget https://raw.githubusercontent.com/Unstructured-IO/unstructured/main/example-docs/example-10k.html -P $docs_dir\n",
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"!wget https://raw.githubusercontent.com/Unstructured-IO/unstructured/main/example-docs/layout-parser-paper.pdf -P $docs_dir"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"jukit_cell_id": "U633RkWjYq"
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},
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"source": [
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"[repo link](https://github.com/Unstructured-IO/unstructured#coffee-getting-started)\n",
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"The easiest way to parse a document in unstructured is to use the partition brick. If you use partition brick, unstructured will detect the file type and route it to the appropriate file-specific partitioning brick. If you are using the partition brick, ensure you first install libmagic using the instructions outlined here partition will always apply the default arguments. If you need advanced features, use a document-specific brick. The partition brick currently works for .txt, .docx, .pptx, .jpg, .png, .eml, .html, and .pdf documents.\n",
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"\n",
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"Requires detectonr2 inference (cuda ?)"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "FJaYuFeL0U"
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},
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"source": [
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"docs_dir=\"unstructured-examples\""
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "9MKaXz7Bi4"
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},
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"source": [
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"#NOTE: needs inference with facebook's detectron2\n",
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"\n",
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"# from unstructured.partition.auto import partition\n",
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"\n",
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"# elements = partition(docs_dir + \"/layout-parser-paper.pdf\")"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"jukit_cell_id": "X4mTVZAzcD"
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},
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"source": [
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"## Unstructured Langchain FileLoader\n",
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"\n",
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"Requires detectron2"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "9k0eAtsfvh"
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},
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"source": [
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"from langchain.document_loaders import UnstructuredFileLoader\n",
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"\n",
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"loader = UnstructuredFileLoader(\"./unstructured-examples/layout-parser-paper.pdf\")\n",
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"\n",
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"docs = loader.load()"
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],
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)\nCell \u001b[0;32mIn[10], line 5\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m UnstructuredFileLoader\n\u001b[1;32m 3\u001b[0m loader \u001b[38;5;241m=\u001b[39m UnstructuredFileLoader(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m./unstructured-examples/layout-parser-paper.pdf\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 5\u001b[0m docs \u001b[38;5;241m=\u001b[39m \u001b[43mloader\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\nFile \u001b[0;32m/data/source/langchain/langchain/document_loaders/unstructured.py:26\u001b[0m, in \u001b[0;36mUnstructuredFileLoader.load\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Load file.\"\"\"\u001b[39;00m\n\u001b[1;32m 24\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01munstructured\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpartition\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mauto\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m partition\n\u001b[0;32m---> 26\u001b[0m elements \u001b[38;5;241m=\u001b[39m \u001b[43mpartition\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfile_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 27\u001b[0m text \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin([\u001b[38;5;28mstr\u001b[39m(el) \u001b[38;5;28;01mfor\u001b[39;00m el \u001b[38;5;129;01min\u001b[39;00m elements])\n\u001b[1;32m 28\u001b[0m metadata \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msource\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfile_path}\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured/partition/auto.py:44\u001b[0m, in \u001b[0;36mpartition\u001b[0;34m(filename, file, include_page_breaks)\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m partition_html(filename\u001b[38;5;241m=\u001b[39mfilename, file\u001b[38;5;241m=\u001b[39mfile, include_page_breaks\u001b[38;5;241m=\u001b[39minclude_page_breaks)\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m filetype \u001b[38;5;241m==\u001b[39m FileType\u001b[38;5;241m.\u001b[39mPDF:\n\u001b[0;32m---> 44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpartition_pdf\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 45\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 46\u001b[0m \u001b[43m \u001b[49m\u001b[43mfile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfile\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 47\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 48\u001b[0m \u001b[43m \u001b[49m\u001b[43minclude_page_breaks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclude_page_breaks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 49\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m (filetype \u001b[38;5;241m==\u001b[39m FileType\u001b[38;5;241m.\u001b[39mPNG) \u001b[38;5;129;01mor\u001b[39;00m (filetype \u001b[38;5;241m==\u001b[39m FileType\u001b[38;5;241m.\u001b[39mJPG):\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m partition_image(\n\u001b[1;32m 52\u001b[0m filename\u001b[38;5;241m=\u001b[39mfilename, \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 53\u001b[0m file\u001b[38;5;241m=\u001b[39mfile, \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 54\u001b[0m url\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 55\u001b[0m include_page_breaks\u001b[38;5;241m=\u001b[39minclude_page_breaks,\n\u001b[1;32m 56\u001b[0m )\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured/partition/pdf.py:35\u001b[0m, in \u001b[0;36mpartition_pdf\u001b[0;34m(filename, file, url, template, token, include_page_breaks)\u001b[0m\n\u001b[1;32m 33\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m template \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 34\u001b[0m template \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlayout/pdf\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m---> 35\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpartition_pdf_or_image\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 36\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 37\u001b[0m \u001b[43m \u001b[49m\u001b[43mfile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfile\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 38\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 39\u001b[0m \u001b[43m \u001b[49m\u001b[43mtemplate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtemplate\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 40\u001b[0m \u001b[43m \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 41\u001b[0m \u001b[43m \u001b[49m\u001b[43minclude_page_breaks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclude_page_breaks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 42\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured/partition/pdf.py:69\u001b[0m, in \u001b[0;36mpartition_pdf_or_image\u001b[0;34m(filename, file, url, template, token, is_image, include_page_breaks)\u001b[0m\n\u001b[1;32m 67\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m warnings\u001b[38;5;241m.\u001b[39mcatch_warnings():\n\u001b[1;32m 68\u001b[0m warnings\u001b[38;5;241m.\u001b[39msimplefilter(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 69\u001b[0m layout_elements \u001b[38;5;241m=\u001b[39m \u001b[43m_partition_pdf_or_image_local\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 70\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 71\u001b[0m \u001b[43m \u001b[49m\u001b[43mfile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfile\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[43m \u001b[49m\u001b[43mtemplate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mout_template\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_image\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_image\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[43m \u001b[49m\u001b[43minclude_page_breaks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclude_page_breaks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 75\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 77\u001b[0m \u001b[38;5;66;03m# NOTE(alan): Remove these lines after different models are handled by routing\u001b[39;00m\n\u001b[1;32m 78\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m template \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcheckbox\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured/partition/pdf.py:133\u001b[0m, in \u001b[0;36m_partition_pdf_or_image_local\u001b[0;34m(filename, file, template, is_image, include_page_breaks)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 125\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\n\u001b[1;32m 126\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThere was a problem importing unstructured_inference module - it may not be installed \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 127\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcorrectly... try running pip install unstructured[local-inference] if you installed \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthe unstructured library as a package. If you cloned the unstructured repository, try \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 129\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrunning make install-local-inference from the root directory of the repository.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 130\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m 132\u001b[0m layout \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 133\u001b[0m \u001b[43mprocess_file_with_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemplate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mis_image\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_image\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m process_data_with_model(file, template, is_image\u001b[38;5;241m=\u001b[39mis_image)\n\u001b[1;32m 136\u001b[0m )\n\u001b[1;32m 138\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m document_to_element_list(layout, include_page_breaks\u001b[38;5;241m=\u001b[39minclude_page_breaks)\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured_inference/inference/layout.py:266\u001b[0m, in \u001b[0;36mprocess_file_with_model\u001b[0;34m(filename, model_name, is_image)\u001b[0m\n\u001b[1;32m 261\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mprocess_file_with_model\u001b[39m(\n\u001b[1;32m 262\u001b[0m filename: \u001b[38;5;28mstr\u001b[39m, model_name: Optional[\u001b[38;5;28mstr\u001b[39m], is_image: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 263\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DocumentLayout:\n\u001b[1;32m 264\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Processes pdf file with name filename into a DocumentLayout by using a model identified by\u001b[39;00m\n\u001b[1;32m 265\u001b[0m \u001b[38;5;124;03m model_name.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 266\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mget_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 267\u001b[0m layout \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 268\u001b[0m DocumentLayout\u001b[38;5;241m.\u001b[39mfrom_image_file(filename, model\u001b[38;5;241m=\u001b[39mmodel)\n\u001b[1;32m 269\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_image\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m DocumentLayout\u001b[38;5;241m.\u001b[39mfrom_file(filename, model\u001b[38;5;241m=\u001b[39mmodel)\n\u001b[1;32m 271\u001b[0m )\n\u001b[1;32m 272\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m layout\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured_inference/models/base.py:14\u001b[0m, in \u001b[0;36mget_model\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m model_name \u001b[38;5;129;01min\u001b[39;00m DETECTRON2_MODEL_TYPES:\n\u001b[1;32m 13\u001b[0m model \u001b[38;5;241m=\u001b[39m UnstructuredDetectronModel()\n\u001b[0;32m---> 14\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minitialize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mDETECTRON2_MODEL_TYPES\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnknownModelException(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnknown model type: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodel_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\nFile \u001b[0;32m~/.pyenv/versions/3.9.11/envs/langchain/lib/python3.9/site-packages/unstructured_inference/models/detectron2.py:76\u001b[0m, in \u001b[0;36mUnstructuredDetectronModel.initialize\u001b[0;34m(self, config_path, model_path, label_map, extra_config, device)\u001b[0m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Loads the detectron2 model using the specified parameters\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_detectron2_available():\n\u001b[0;32m---> 76\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[1;32m 77\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to load the Detectron2 model. Ensure that the Detectron2 \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 78\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodule is correctly installed.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 79\u001b[0m )\n\u001b[1;32m 81\u001b[0m config_path_str \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mstr\u001b[39m(config_path)\n\u001b[1;32m 82\u001b[0m model_path_str: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m model_path \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(model_path)\n\n\u001b[0;31mImportError\u001b[0m: Failed to load the Detectron2 model. Ensure that the Detectron2 module is correctly installed.\n"
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}
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],
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"execution_count": 2
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},
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{
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"cell_type": "code",
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"metadata": {
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"jukit_cell_id": "1lKP9jNDd4"
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},
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"source": [],
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"outputs": [],
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"execution_count": null
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}
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],
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "python",
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"language": "python",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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} |